Instructions to use Priyanship/eval_transliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Priyanship/eval_transliterated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Priyanship/eval_transliterated")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Priyanship/eval_transliterated") model = AutoModelForCTC.from_pretrained("Priyanship/eval_transliterated") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9228c116f1a91b62147c41848e293e6d694510ae43beefec6572f063b8713db8
- Size of remote file:
- 5.5 kB
- SHA256:
- 954d7a455e31bcebf83d96e44fe9e8f1ef759e4b68320f663497b83816219fe0
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